{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd \n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>日期</th>\n",
       "      <th>点击</th>\n",
       "      <th>收藏</th>\n",
       "      <th>加购</th>\n",
       "      <th>购买</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014-11-18</td>\n",
       "      <td>345855</td>\n",
       "      <td>6904</td>\n",
       "      <td>10212</td>\n",
       "      <td>3730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2014-11-19</td>\n",
       "      <td>337870</td>\n",
       "      <td>7152</td>\n",
       "      <td>10115</td>\n",
       "      <td>3686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2014-11-20</td>\n",
       "      <td>332792</td>\n",
       "      <td>7167</td>\n",
       "      <td>10008</td>\n",
       "      <td>3462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014-11-21</td>\n",
       "      <td>314572</td>\n",
       "      <td>6832</td>\n",
       "      <td>8679</td>\n",
       "      <td>3021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014-11-22</td>\n",
       "      <td>340563</td>\n",
       "      <td>7252</td>\n",
       "      <td>9970</td>\n",
       "      <td>3570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2014-11-23</td>\n",
       "      <td>361221</td>\n",
       "      <td>7702</td>\n",
       "      <td>10432</td>\n",
       "      <td>3347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2014-11-24</td>\n",
       "      <td>357192</td>\n",
       "      <td>7333</td>\n",
       "      <td>10391</td>\n",
       "      <td>3426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2014-11-25</td>\n",
       "      <td>349392</td>\n",
       "      <td>7492</td>\n",
       "      <td>9891</td>\n",
       "      <td>3464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2014-11-26</td>\n",
       "      <td>340621</td>\n",
       "      <td>7324</td>\n",
       "      <td>9378</td>\n",
       "      <td>3573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2014-11-27</td>\n",
       "      <td>350040</td>\n",
       "      <td>7699</td>\n",
       "      <td>9975</td>\n",
       "      <td>3670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2014-11-28</td>\n",
       "      <td>321813</td>\n",
       "      <td>6484</td>\n",
       "      <td>9123</td>\n",
       "      <td>3218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2014-11-29</td>\n",
       "      <td>344127</td>\n",
       "      <td>7214</td>\n",
       "      <td>10145</td>\n",
       "      <td>3211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2014-11-30</td>\n",
       "      <td>379439</td>\n",
       "      <td>7786</td>\n",
       "      <td>10779</td>\n",
       "      <td>3616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2014-12-01</td>\n",
       "      <td>372095</td>\n",
       "      <td>7319</td>\n",
       "      <td>11288</td>\n",
       "      <td>3909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2014-12-02</td>\n",
       "      <td>382052</td>\n",
       "      <td>8022</td>\n",
       "      <td>11521</td>\n",
       "      <td>3621</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2014-12-03</td>\n",
       "      <td>387497</td>\n",
       "      <td>8492</td>\n",
       "      <td>11732</td>\n",
       "      <td>3885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2014-12-04</td>\n",
       "      <td>376307</td>\n",
       "      <td>8559</td>\n",
       "      <td>11395</td>\n",
       "      <td>3691</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2014-12-05</td>\n",
       "      <td>340976</td>\n",
       "      <td>7474</td>\n",
       "      <td>10109</td>\n",
       "      <td>3319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2014-12-06</td>\n",
       "      <td>367126</td>\n",
       "      <td>8323</td>\n",
       "      <td>10889</td>\n",
       "      <td>3272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2014-12-07</td>\n",
       "      <td>376596</td>\n",
       "      <td>8632</td>\n",
       "      <td>11267</td>\n",
       "      <td>3256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2014-12-08</td>\n",
       "      <td>364097</td>\n",
       "      <td>8236</td>\n",
       "      <td>10915</td>\n",
       "      <td>3419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2014-12-09</td>\n",
       "      <td>374261</td>\n",
       "      <td>8552</td>\n",
       "      <td>11763</td>\n",
       "      <td>3449</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2014-12-10</td>\n",
       "      <td>397661</td>\n",
       "      <td>8753</td>\n",
       "      <td>12280</td>\n",
       "      <td>3216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2014-12-11</td>\n",
       "      <td>460329</td>\n",
       "      <td>9310</td>\n",
       "      <td>15643</td>\n",
       "      <td>3226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2014-12-12</td>\n",
       "      <td>641507</td>\n",
       "      <td>10446</td>\n",
       "      <td>24508</td>\n",
       "      <td>15251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2014-12-13</td>\n",
       "      <td>385337</td>\n",
       "      <td>7859</td>\n",
       "      <td>10486</td>\n",
       "      <td>3478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2014-12-14</td>\n",
       "      <td>380717</td>\n",
       "      <td>8128</td>\n",
       "      <td>10213</td>\n",
       "      <td>3483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2014-12-15</td>\n",
       "      <td>376624</td>\n",
       "      <td>7758</td>\n",
       "      <td>10210</td>\n",
       "      <td>3764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2014-12-16</td>\n",
       "      <td>373399</td>\n",
       "      <td>7749</td>\n",
       "      <td>10166</td>\n",
       "      <td>3771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>363757</td>\n",
       "      <td>7163</td>\n",
       "      <td>10256</td>\n",
       "      <td>3615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2014-12-18</td>\n",
       "      <td>354746</td>\n",
       "      <td>7440</td>\n",
       "      <td>9825</td>\n",
       "      <td>3586</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            日期      点击     收藏     加购     购买\n",
       "0   2014-11-18  345855   6904  10212   3730\n",
       "1   2014-11-19  337870   7152  10115   3686\n",
       "2   2014-11-20  332792   7167  10008   3462\n",
       "3   2014-11-21  314572   6832   8679   3021\n",
       "4   2014-11-22  340563   7252   9970   3570\n",
       "5   2014-11-23  361221   7702  10432   3347\n",
       "6   2014-11-24  357192   7333  10391   3426\n",
       "7   2014-11-25  349392   7492   9891   3464\n",
       "8   2014-11-26  340621   7324   9378   3573\n",
       "9   2014-11-27  350040   7699   9975   3670\n",
       "10  2014-11-28  321813   6484   9123   3218\n",
       "11  2014-11-29  344127   7214  10145   3211\n",
       "12  2014-11-30  379439   7786  10779   3616\n",
       "13  2014-12-01  372095   7319  11288   3909\n",
       "14  2014-12-02  382052   8022  11521   3621\n",
       "15  2014-12-03  387497   8492  11732   3885\n",
       "16  2014-12-04  376307   8559  11395   3691\n",
       "17  2014-12-05  340976   7474  10109   3319\n",
       "18  2014-12-06  367126   8323  10889   3272\n",
       "19  2014-12-07  376596   8632  11267   3256\n",
       "20  2014-12-08  364097   8236  10915   3419\n",
       "21  2014-12-09  374261   8552  11763   3449\n",
       "22  2014-12-10  397661   8753  12280   3216\n",
       "23  2014-12-11  460329   9310  15643   3226\n",
       "24  2014-12-12  641507  10446  24508  15251\n",
       "25  2014-12-13  385337   7859  10486   3478\n",
       "26  2014-12-14  380717   8128  10213   3483\n",
       "27  2014-12-15  376624   7758  10210   3764\n",
       "28  2014-12-16  373399   7749  10166   3771\n",
       "29  2014-12-17  363757   7163  10256   3615\n",
       "30  2014-12-18  354746   7440   9825   3586"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_excel('./每日点击收藏加购和购买的量.xlsx')\n",
    "data = pd.DataFrame(data = data)\n",
    "data.columns=[['日期','点击','收藏','加购','购买']]\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pylab import mpl\n",
    "mpl.rcParams['font.sans-serif'] = ['SimHei']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2c24d212250>"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x648 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,((ax11,ax12),(ax21,ax22)) = plt.subplots(2,2) # 返回子视图\n",
    "\n",
    "fig.set_figwidth(12)\n",
    "fig.set_figheight(9)\n",
    "\n",
    "ax11.plot(data[['点击']],marker = 'o')\n",
    "ax11.xticks = data[['日期']] \n",
    "ax11.legend(['点击'])\n",
    "ax12.plot(data[['收藏']],marker = 'o')\n",
    "ax12.legend(['收藏'])\n",
    "ax21.plot(data[['加购']],marker = 'o')\n",
    "ax21.legend(['加购'])\n",
    "ax22.plot(data[['购买']],marker = 'o')\n",
    "ax22.legend(['购买']) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>日期</th>\n",
       "      <th>点击</th>\n",
       "      <th>收藏</th>\n",
       "      <th>加购</th>\n",
       "      <th>购买</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014-11-18</td>\n",
       "      <td>6340</td>\n",
       "      <td>1516</td>\n",
       "      <td>2221</td>\n",
       "      <td>1539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2014-11-19</td>\n",
       "      <td>6418</td>\n",
       "      <td>1499</td>\n",
       "      <td>2201</td>\n",
       "      <td>1511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2014-11-20</td>\n",
       "      <td>6332</td>\n",
       "      <td>1502</td>\n",
       "      <td>2210</td>\n",
       "      <td>1492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014-11-21</td>\n",
       "      <td>6275</td>\n",
       "      <td>1439</td>\n",
       "      <td>2023</td>\n",
       "      <td>1330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014-11-22</td>\n",
       "      <td>6184</td>\n",
       "      <td>1479</td>\n",
       "      <td>2100</td>\n",
       "      <td>1411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2014-11-23</td>\n",
       "      <td>6371</td>\n",
       "      <td>1567</td>\n",
       "      <td>2187</td>\n",
       "      <td>1436</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2014-11-24</td>\n",
       "      <td>6511</td>\n",
       "      <td>1542</td>\n",
       "      <td>2236</td>\n",
       "      <td>1524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2014-11-25</td>\n",
       "      <td>6346</td>\n",
       "      <td>1561</td>\n",
       "      <td>2160</td>\n",
       "      <td>1497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2014-11-26</td>\n",
       "      <td>6353</td>\n",
       "      <td>1539</td>\n",
       "      <td>2150</td>\n",
       "      <td>1487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2014-11-27</td>\n",
       "      <td>6357</td>\n",
       "      <td>1493</td>\n",
       "      <td>2203</td>\n",
       "      <td>1527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2014-11-28</td>\n",
       "      <td>6185</td>\n",
       "      <td>1479</td>\n",
       "      <td>2063</td>\n",
       "      <td>1442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2014-11-29</td>\n",
       "      <td>6220</td>\n",
       "      <td>1464</td>\n",
       "      <td>2057</td>\n",
       "      <td>1377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2014-11-30</td>\n",
       "      <td>6378</td>\n",
       "      <td>1590</td>\n",
       "      <td>2317</td>\n",
       "      <td>1534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2014-12-01</td>\n",
       "      <td>6543</td>\n",
       "      <td>1588</td>\n",
       "      <td>2428</td>\n",
       "      <td>1657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2014-12-02</td>\n",
       "      <td>6547</td>\n",
       "      <td>1731</td>\n",
       "      <td>2510</td>\n",
       "      <td>1585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2014-12-03</td>\n",
       "      <td>6581</td>\n",
       "      <td>1735</td>\n",
       "      <td>2464</td>\n",
       "      <td>1697</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2014-12-04</td>\n",
       "      <td>6528</td>\n",
       "      <td>1711</td>\n",
       "      <td>2518</td>\n",
       "      <td>1585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2014-12-05</td>\n",
       "      <td>6364</td>\n",
       "      <td>1590</td>\n",
       "      <td>2303</td>\n",
       "      <td>1493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2014-12-06</td>\n",
       "      <td>6438</td>\n",
       "      <td>1665</td>\n",
       "      <td>2411</td>\n",
       "      <td>1452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2014-12-07</td>\n",
       "      <td>6420</td>\n",
       "      <td>1680</td>\n",
       "      <td>2411</td>\n",
       "      <td>1403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2014-12-08</td>\n",
       "      <td>6560</td>\n",
       "      <td>1652</td>\n",
       "      <td>2480</td>\n",
       "      <td>1551</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2014-12-09</td>\n",
       "      <td>6563</td>\n",
       "      <td>1696</td>\n",
       "      <td>2487</td>\n",
       "      <td>1429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2014-12-10</td>\n",
       "      <td>6649</td>\n",
       "      <td>1733</td>\n",
       "      <td>2632</td>\n",
       "      <td>1442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2014-12-11</td>\n",
       "      <td>6892</td>\n",
       "      <td>1891</td>\n",
       "      <td>3078</td>\n",
       "      <td>1449</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2014-12-12</td>\n",
       "      <td>7718</td>\n",
       "      <td>2095</td>\n",
       "      <td>3958</td>\n",
       "      <td>3897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2014-12-13</td>\n",
       "      <td>6774</td>\n",
       "      <td>1656</td>\n",
       "      <td>2420</td>\n",
       "      <td>1549</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2014-12-14</td>\n",
       "      <td>6668</td>\n",
       "      <td>1636</td>\n",
       "      <td>2371</td>\n",
       "      <td>1506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2014-12-15</td>\n",
       "      <td>6784</td>\n",
       "      <td>1628</td>\n",
       "      <td>2396</td>\n",
       "      <td>1627</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2014-12-16</td>\n",
       "      <td>6726</td>\n",
       "      <td>1642</td>\n",
       "      <td>2349</td>\n",
       "      <td>1650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>6636</td>\n",
       "      <td>1553</td>\n",
       "      <td>2298</td>\n",
       "      <td>1570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2014-12-18</td>\n",
       "      <td>6576</td>\n",
       "      <td>1520</td>\n",
       "      <td>2288</td>\n",
       "      <td>1552</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            日期    点击    收藏    加购    购买\n",
       "0   2014-11-18  6340  1516  2221  1539\n",
       "1   2014-11-19  6418  1499  2201  1511\n",
       "2   2014-11-20  6332  1502  2210  1492\n",
       "3   2014-11-21  6275  1439  2023  1330\n",
       "4   2014-11-22  6184  1479  2100  1411\n",
       "5   2014-11-23  6371  1567  2187  1436\n",
       "6   2014-11-24  6511  1542  2236  1524\n",
       "7   2014-11-25  6346  1561  2160  1497\n",
       "8   2014-11-26  6353  1539  2150  1487\n",
       "9   2014-11-27  6357  1493  2203  1527\n",
       "10  2014-11-28  6185  1479  2063  1442\n",
       "11  2014-11-29  6220  1464  2057  1377\n",
       "12  2014-11-30  6378  1590  2317  1534\n",
       "13  2014-12-01  6543  1588  2428  1657\n",
       "14  2014-12-02  6547  1731  2510  1585\n",
       "15  2014-12-03  6581  1735  2464  1697\n",
       "16  2014-12-04  6528  1711  2518  1585\n",
       "17  2014-12-05  6364  1590  2303  1493\n",
       "18  2014-12-06  6438  1665  2411  1452\n",
       "19  2014-12-07  6420  1680  2411  1403\n",
       "20  2014-12-08  6560  1652  2480  1551\n",
       "21  2014-12-09  6563  1696  2487  1429\n",
       "22  2014-12-10  6649  1733  2632  1442\n",
       "23  2014-12-11  6892  1891  3078  1449\n",
       "24  2014-12-12  7718  2095  3958  3897\n",
       "25  2014-12-13  6774  1656  2420  1549\n",
       "26  2014-12-14  6668  1636  2371  1506\n",
       "27  2014-12-15  6784  1628  2396  1627\n",
       "28  2014-12-16  6726  1642  2349  1650\n",
       "29  2014-12-17  6636  1553  2298  1570\n",
       "30  2014-12-18  6576  1520  2288  1552"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_01 = pd.read_excel('./每天有点击收藏加购支付行为的用户数量(改).xlsx') \n",
    "data_01"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2c24d61a0a0>"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x648 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pylab import mpl\n",
    "mpl.rcParams['font.sans-serif'] = ['SimHei']\n",
    "\n",
    "fig,((ax11,ax12),(ax21,ax22)) = plt.subplots(2,2) # 返回子视图\n",
    "\n",
    "fig.set_figwidth(12)\n",
    "fig.set_figheight(9)\n",
    "\n",
    "ax11.plot(data_01[['点击']],marker = 'o')\n",
    "ax11.xticks = data_01[['日期']] \n",
    "ax11.legend(['点击'])\n",
    "ax12.plot(data_01[['收藏']],marker = 'o')\n",
    "ax12.legend(['收藏'])\n",
    "ax21.plot(data_01[['加购']],marker = 'o')\n",
    "ax21.legend(['加购'])\n",
    "ax22.plot(data_01[['购买']],marker = 'o')\n",
    "ax22.legend(['购买']) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>item_category</th>\n",
       "      <th>该商品类目的商品数量</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5894</td>\n",
       "      <td>83758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1863</td>\n",
       "      <td>83354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>13230</td>\n",
       "      <td>74067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6513</td>\n",
       "      <td>65045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5027</td>\n",
       "      <td>60323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8911</th>\n",
       "      <td>8553</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8912</th>\n",
       "      <td>8544</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8913</th>\n",
       "      <td>8456</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8914</th>\n",
       "      <td>8453</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8915</th>\n",
       "      <td>7073</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8916 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      item_category  该商品类目的商品数量\n",
       "0              5894       83758\n",
       "1              1863       83354\n",
       "2             13230       74067\n",
       "3              6513       65045\n",
       "4              5027       60323\n",
       "...             ...         ...\n",
       "8911           8553           1\n",
       "8912           8544           1\n",
       "8913           8456           1\n",
       "8914           8453           1\n",
       "8915           7073           1\n",
       "\n",
       "[8916 rows x 2 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#每个商品类目的商品的数量\n",
    "data_02 = pd.read_excel('./商品类目的商品数量.xlsx') \n",
    "data_02"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>item_category</th>\n",
       "      <th>点击</th>\n",
       "      <th>收藏</th>\n",
       "      <th>加购</th>\n",
       "      <th>支付</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1136</td>\n",
       "      <td>1863</td>\n",
       "      <td>371738.0</td>\n",
       "      <td>10200.0</td>\n",
       "      <td>9309.0</td>\n",
       "      <td>2000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8371</td>\n",
       "      <td>13230</td>\n",
       "      <td>342694.0</td>\n",
       "      <td>7226.0</td>\n",
       "      <td>6012.0</td>\n",
       "      <td>841.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3148</td>\n",
       "      <td>5027</td>\n",
       "      <td>320870.0</td>\n",
       "      <td>6988.0</td>\n",
       "      <td>5564.0</td>\n",
       "      <td>858.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3708</td>\n",
       "      <td>5894</td>\n",
       "      <td>314784.0</td>\n",
       "      <td>7850.0</td>\n",
       "      <td>6615.0</td>\n",
       "      <td>958.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4094</td>\n",
       "      <td>6513</td>\n",
       "      <td>281370.0</td>\n",
       "      <td>6688.0</td>\n",
       "      <td>6651.0</td>\n",
       "      <td>1059.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3394</td>\n",
       "      <td>5399</td>\n",
       "      <td>268639.0</td>\n",
       "      <td>6616.0</td>\n",
       "      <td>5430.0</td>\n",
       "      <td>1054.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7098</td>\n",
       "      <td>11279</td>\n",
       "      <td>177961.0</td>\n",
       "      <td>4687.0</td>\n",
       "      <td>3686.0</td>\n",
       "      <td>722.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1758</td>\n",
       "      <td>2825</td>\n",
       "      <td>155949.0</td>\n",
       "      <td>3360.0</td>\n",
       "      <td>3692.0</td>\n",
       "      <td>625.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>3284</td>\n",
       "      <td>5232</td>\n",
       "      <td>135506.0</td>\n",
       "      <td>2597.0</td>\n",
       "      <td>4486.0</td>\n",
       "      <td>1611.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>6844</td>\n",
       "      <td>10894</td>\n",
       "      <td>131221.0</td>\n",
       "      <td>2802.0</td>\n",
       "      <td>3894.0</td>\n",
       "      <td>865.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2744</td>\n",
       "      <td>4370</td>\n",
       "      <td>115048.0</td>\n",
       "      <td>2481.0</td>\n",
       "      <td>3424.0</td>\n",
       "      <td>775.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>3578</td>\n",
       "      <td>5689</td>\n",
       "      <td>109697.0</td>\n",
       "      <td>2908.0</td>\n",
       "      <td>2861.0</td>\n",
       "      <td>563.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>3777</td>\n",
       "      <td>6000</td>\n",
       "      <td>105163.0</td>\n",
       "      <td>876.0</td>\n",
       "      <td>1266.0</td>\n",
       "      <td>301.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1911</td>\n",
       "      <td>3064</td>\n",
       "      <td>105034.0</td>\n",
       "      <td>3047.0</td>\n",
       "      <td>3918.0</td>\n",
       "      <td>806.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>3392</td>\n",
       "      <td>5395</td>\n",
       "      <td>93082.0</td>\n",
       "      <td>1915.0</td>\n",
       "      <td>1719.0</td>\n",
       "      <td>162.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>8914</td>\n",
       "      <td>14079</td>\n",
       "      <td>93007.0</td>\n",
       "      <td>2189.0</td>\n",
       "      <td>2515.0</td>\n",
       "      <td>479.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>6532</td>\n",
       "      <td>10392</td>\n",
       "      <td>91341.0</td>\n",
       "      <td>2089.0</td>\n",
       "      <td>2733.0</td>\n",
       "      <td>866.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>3985</td>\n",
       "      <td>6344</td>\n",
       "      <td>85369.0</td>\n",
       "      <td>1660.0</td>\n",
       "      <td>3822.0</td>\n",
       "      <td>2208.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2106</td>\n",
       "      <td>3381</td>\n",
       "      <td>84833.0</td>\n",
       "      <td>1720.0</td>\n",
       "      <td>1627.0</td>\n",
       "      <td>406.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>5976</td>\n",
       "      <td>9516</td>\n",
       "      <td>81285.0</td>\n",
       "      <td>1230.0</td>\n",
       "      <td>3340.0</td>\n",
       "      <td>828.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>7283</td>\n",
       "      <td>11552</td>\n",
       "      <td>74627.0</td>\n",
       "      <td>1494.0</td>\n",
       "      <td>1654.0</td>\n",
       "      <td>439.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>3809</td>\n",
       "      <td>6054</td>\n",
       "      <td>73914.0</td>\n",
       "      <td>2168.0</td>\n",
       "      <td>1592.0</td>\n",
       "      <td>374.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2253</td>\n",
       "      <td>3628</td>\n",
       "      <td>70260.0</td>\n",
       "      <td>1221.0</td>\n",
       "      <td>1641.0</td>\n",
       "      <td>583.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>3467</td>\n",
       "      <td>5503</td>\n",
       "      <td>68811.0</td>\n",
       "      <td>1944.0</td>\n",
       "      <td>1682.0</td>\n",
       "      <td>328.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>7471</td>\n",
       "      <td>11824</td>\n",
       "      <td>67306.0</td>\n",
       "      <td>1329.0</td>\n",
       "      <td>1896.0</td>\n",
       "      <td>578.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>653</td>\n",
       "      <td>1083</td>\n",
       "      <td>66066.0</td>\n",
       "      <td>1385.0</td>\n",
       "      <td>1801.0</td>\n",
       "      <td>530.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>6619</td>\n",
       "      <td>10533</td>\n",
       "      <td>64242.0</td>\n",
       "      <td>1490.0</td>\n",
       "      <td>1203.0</td>\n",
       "      <td>184.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>3315</td>\n",
       "      <td>5271</td>\n",
       "      <td>64097.0</td>\n",
       "      <td>1484.0</td>\n",
       "      <td>1603.0</td>\n",
       "      <td>339.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>5579</td>\n",
       "      <td>8877</td>\n",
       "      <td>63396.0</td>\n",
       "      <td>1247.0</td>\n",
       "      <td>1974.0</td>\n",
       "      <td>1072.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2361</td>\n",
       "      <td>3783</td>\n",
       "      <td>62689.0</td>\n",
       "      <td>1553.0</td>\n",
       "      <td>1657.0</td>\n",
       "      <td>375.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Unnamed: 0  item_category        点击       收藏      加购      支付\n",
       "0         1136           1863  371738.0  10200.0  9309.0  2000.0\n",
       "1         8371          13230  342694.0   7226.0  6012.0   841.0\n",
       "2         3148           5027  320870.0   6988.0  5564.0   858.0\n",
       "3         3708           5894  314784.0   7850.0  6615.0   958.0\n",
       "4         4094           6513  281370.0   6688.0  6651.0  1059.0\n",
       "5         3394           5399  268639.0   6616.0  5430.0  1054.0\n",
       "6         7098          11279  177961.0   4687.0  3686.0   722.0\n",
       "7         1758           2825  155949.0   3360.0  3692.0   625.0\n",
       "8         3284           5232  135506.0   2597.0  4486.0  1611.0\n",
       "9         6844          10894  131221.0   2802.0  3894.0   865.0\n",
       "10        2744           4370  115048.0   2481.0  3424.0   775.0\n",
       "11        3578           5689  109697.0   2908.0  2861.0   563.0\n",
       "12        3777           6000  105163.0    876.0  1266.0   301.0\n",
       "13        1911           3064  105034.0   3047.0  3918.0   806.0\n",
       "14        3392           5395   93082.0   1915.0  1719.0   162.0\n",
       "15        8914          14079   93007.0   2189.0  2515.0   479.0\n",
       "16        6532          10392   91341.0   2089.0  2733.0   866.0\n",
       "17        3985           6344   85369.0   1660.0  3822.0  2208.0\n",
       "18        2106           3381   84833.0   1720.0  1627.0   406.0\n",
       "19        5976           9516   81285.0   1230.0  3340.0   828.0\n",
       "20        7283          11552   74627.0   1494.0  1654.0   439.0\n",
       "21        3809           6054   73914.0   2168.0  1592.0   374.0\n",
       "22        2253           3628   70260.0   1221.0  1641.0   583.0\n",
       "23        3467           5503   68811.0   1944.0  1682.0   328.0\n",
       "24        7471          11824   67306.0   1329.0  1896.0   578.0\n",
       "25         653           1083   66066.0   1385.0  1801.0   530.0\n",
       "26        6619          10533   64242.0   1490.0  1203.0   184.0\n",
       "27        3315           5271   64097.0   1484.0  1603.0   339.0\n",
       "28        5579           8877   63396.0   1247.0  1974.0  1072.0\n",
       "29        2361           3783   62689.0   1553.0  1657.0   375.0"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#点击最高的三十个商品品类分别是\n",
    "data_03 = pd.read_csv('./每一类商品的点击量、收藏量、加购量、购买量.csv')\n",
    "data_03.head(30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>item_category</th>\n",
       "      <th>点击</th>\n",
       "      <th>收藏</th>\n",
       "      <th>加购</th>\n",
       "      <th>支付</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>3985</td>\n",
       "      <td>6344</td>\n",
       "      <td>85369.0</td>\n",
       "      <td>1660.0</td>\n",
       "      <td>3822.0</td>\n",
       "      <td>2208.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1136</td>\n",
       "      <td>1863</td>\n",
       "      <td>371738.0</td>\n",
       "      <td>10200.0</td>\n",
       "      <td>9309.0</td>\n",
       "      <td>2000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>3284</td>\n",
       "      <td>5232</td>\n",
       "      <td>135506.0</td>\n",
       "      <td>2597.0</td>\n",
       "      <td>4486.0</td>\n",
       "      <td>1611.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>4394</td>\n",
       "      <td>6977</td>\n",
       "      <td>22806.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>1324.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>5579</td>\n",
       "      <td>8877</td>\n",
       "      <td>63396.0</td>\n",
       "      <td>1247.0</td>\n",
       "      <td>1974.0</td>\n",
       "      <td>1072.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4094</td>\n",
       "      <td>6513</td>\n",
       "      <td>281370.0</td>\n",
       "      <td>6688.0</td>\n",
       "      <td>6651.0</td>\n",
       "      <td>1059.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3394</td>\n",
       "      <td>5399</td>\n",
       "      <td>268639.0</td>\n",
       "      <td>6616.0</td>\n",
       "      <td>5430.0</td>\n",
       "      <td>1054.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>2132</td>\n",
       "      <td>3424</td>\n",
       "      <td>51001.0</td>\n",
       "      <td>773.0</td>\n",
       "      <td>1498.0</td>\n",
       "      <td>1053.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2164</td>\n",
       "      <td>3472</td>\n",
       "      <td>51456.0</td>\n",
       "      <td>823.0</td>\n",
       "      <td>1707.0</td>\n",
       "      <td>1038.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>4996</td>\n",
       "      <td>7957</td>\n",
       "      <td>42555.0</td>\n",
       "      <td>883.0</td>\n",
       "      <td>2745.0</td>\n",
       "      <td>997.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3708</td>\n",
       "      <td>5894</td>\n",
       "      <td>314784.0</td>\n",
       "      <td>7850.0</td>\n",
       "      <td>6615.0</td>\n",
       "      <td>958.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>1124</td>\n",
       "      <td>1838</td>\n",
       "      <td>52076.0</td>\n",
       "      <td>850.0</td>\n",
       "      <td>1687.0</td>\n",
       "      <td>919.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>6532</td>\n",
       "      <td>10392</td>\n",
       "      <td>91341.0</td>\n",
       "      <td>2089.0</td>\n",
       "      <td>2733.0</td>\n",
       "      <td>866.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>6844</td>\n",
       "      <td>10894</td>\n",
       "      <td>131221.0</td>\n",
       "      <td>2802.0</td>\n",
       "      <td>3894.0</td>\n",
       "      <td>865.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3148</td>\n",
       "      <td>5027</td>\n",
       "      <td>320870.0</td>\n",
       "      <td>6988.0</td>\n",
       "      <td>5564.0</td>\n",
       "      <td>858.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8371</td>\n",
       "      <td>13230</td>\n",
       "      <td>342694.0</td>\n",
       "      <td>7226.0</td>\n",
       "      <td>6012.0</td>\n",
       "      <td>841.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>5976</td>\n",
       "      <td>9516</td>\n",
       "      <td>81285.0</td>\n",
       "      <td>1230.0</td>\n",
       "      <td>3340.0</td>\n",
       "      <td>828.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1911</td>\n",
       "      <td>3064</td>\n",
       "      <td>105034.0</td>\n",
       "      <td>3047.0</td>\n",
       "      <td>3918.0</td>\n",
       "      <td>806.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2744</td>\n",
       "      <td>4370</td>\n",
       "      <td>115048.0</td>\n",
       "      <td>2481.0</td>\n",
       "      <td>3424.0</td>\n",
       "      <td>775.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7098</td>\n",
       "      <td>11279</td>\n",
       "      <td>177961.0</td>\n",
       "      <td>4687.0</td>\n",
       "      <td>3686.0</td>\n",
       "      <td>722.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1758</td>\n",
       "      <td>2825</td>\n",
       "      <td>155949.0</td>\n",
       "      <td>3360.0</td>\n",
       "      <td>3692.0</td>\n",
       "      <td>625.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>6556</td>\n",
       "      <td>10431</td>\n",
       "      <td>40601.0</td>\n",
       "      <td>499.0</td>\n",
       "      <td>1489.0</td>\n",
       "      <td>614.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2253</td>\n",
       "      <td>3628</td>\n",
       "      <td>70260.0</td>\n",
       "      <td>1221.0</td>\n",
       "      <td>1641.0</td>\n",
       "      <td>583.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>4868</td>\n",
       "      <td>7767</td>\n",
       "      <td>25459.0</td>\n",
       "      <td>654.0</td>\n",
       "      <td>1076.0</td>\n",
       "      <td>578.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>7471</td>\n",
       "      <td>11824</td>\n",
       "      <td>67306.0</td>\n",
       "      <td>1329.0</td>\n",
       "      <td>1896.0</td>\n",
       "      <td>578.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>1862</td>\n",
       "      <td>2993</td>\n",
       "      <td>49014.0</td>\n",
       "      <td>711.0</td>\n",
       "      <td>1252.0</td>\n",
       "      <td>572.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>3578</td>\n",
       "      <td>5689</td>\n",
       "      <td>109697.0</td>\n",
       "      <td>2908.0</td>\n",
       "      <td>2861.0</td>\n",
       "      <td>563.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>7273</td>\n",
       "      <td>11537</td>\n",
       "      <td>19334.0</td>\n",
       "      <td>336.0</td>\n",
       "      <td>1227.0</td>\n",
       "      <td>548.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>5193</td>\n",
       "      <td>8291</td>\n",
       "      <td>37585.0</td>\n",
       "      <td>743.0</td>\n",
       "      <td>1365.0</td>\n",
       "      <td>545.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2287</td>\n",
       "      <td>3673</td>\n",
       "      <td>54874.0</td>\n",
       "      <td>977.0</td>\n",
       "      <td>1419.0</td>\n",
       "      <td>534.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Unnamed: 0  item_category        点击       收藏      加购      支付\n",
       "17        3985           6344   85369.0   1660.0  3822.0  2208.0\n",
       "0         1136           1863  371738.0  10200.0  9309.0  2000.0\n",
       "8         3284           5232  135506.0   2597.0  4486.0  1611.0\n",
       "87        4394           6977   22806.0    273.0  2007.0  1324.0\n",
       "28        5579           8877   63396.0   1247.0  1974.0  1072.0\n",
       "4         4094           6513  281370.0   6688.0  6651.0  1059.0\n",
       "5         3394           5399  268639.0   6616.0  5430.0  1054.0\n",
       "36        2132           3424   51001.0    773.0  1498.0  1053.0\n",
       "35        2164           3472   51456.0    823.0  1707.0  1038.0\n",
       "43        4996           7957   42555.0    883.0  2745.0   997.0\n",
       "3         3708           5894  314784.0   7850.0  6615.0   958.0\n",
       "34        1124           1838   52076.0    850.0  1687.0   919.0\n",
       "16        6532          10392   91341.0   2089.0  2733.0   866.0\n",
       "9         6844          10894  131221.0   2802.0  3894.0   865.0\n",
       "2         3148           5027  320870.0   6988.0  5564.0   858.0\n",
       "1         8371          13230  342694.0   7226.0  6012.0   841.0\n",
       "19        5976           9516   81285.0   1230.0  3340.0   828.0\n",
       "13        1911           3064  105034.0   3047.0  3918.0   806.0\n",
       "10        2744           4370  115048.0   2481.0  3424.0   775.0\n",
       "6         7098          11279  177961.0   4687.0  3686.0   722.0\n",
       "7         1758           2825  155949.0   3360.0  3692.0   625.0\n",
       "48        6556          10431   40601.0    499.0  1489.0   614.0\n",
       "22        2253           3628   70260.0   1221.0  1641.0   583.0\n",
       "74        4868           7767   25459.0    654.0  1076.0   578.0\n",
       "24        7471          11824   67306.0   1329.0  1896.0   578.0\n",
       "38        1862           2993   49014.0    711.0  1252.0   572.0\n",
       "11        3578           5689  109697.0   2908.0  2861.0   563.0\n",
       "99        7273          11537   19334.0    336.0  1227.0   548.0\n",
       "50        5193           8291   37585.0    743.0  1365.0   545.0\n",
       "33        2287           3673   54874.0    977.0  1419.0   534.0"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#购买最多的三十个商品品类分别是以下几个\n",
    "data_03.sort_values('支付',ascending=False,inplace=True)\n",
    "data_03.head(30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>item_category</th>\n",
       "      <th>点击</th>\n",
       "      <th>收藏</th>\n",
       "      <th>加购</th>\n",
       "      <th>支付</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1136</td>\n",
       "      <td>1863</td>\n",
       "      <td>371738.0</td>\n",
       "      <td>10200.0</td>\n",
       "      <td>9309.0</td>\n",
       "      <td>2000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3708</td>\n",
       "      <td>5894</td>\n",
       "      <td>314784.0</td>\n",
       "      <td>7850.0</td>\n",
       "      <td>6615.0</td>\n",
       "      <td>958.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8371</td>\n",
       "      <td>13230</td>\n",
       "      <td>342694.0</td>\n",
       "      <td>7226.0</td>\n",
       "      <td>6012.0</td>\n",
       "      <td>841.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3148</td>\n",
       "      <td>5027</td>\n",
       "      <td>320870.0</td>\n",
       "      <td>6988.0</td>\n",
       "      <td>5564.0</td>\n",
       "      <td>858.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4094</td>\n",
       "      <td>6513</td>\n",
       "      <td>281370.0</td>\n",
       "      <td>6688.0</td>\n",
       "      <td>6651.0</td>\n",
       "      <td>1059.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3394</td>\n",
       "      <td>5399</td>\n",
       "      <td>268639.0</td>\n",
       "      <td>6616.0</td>\n",
       "      <td>5430.0</td>\n",
       "      <td>1054.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7098</td>\n",
       "      <td>11279</td>\n",
       "      <td>177961.0</td>\n",
       "      <td>4687.0</td>\n",
       "      <td>3686.0</td>\n",
       "      <td>722.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1758</td>\n",
       "      <td>2825</td>\n",
       "      <td>155949.0</td>\n",
       "      <td>3360.0</td>\n",
       "      <td>3692.0</td>\n",
       "      <td>625.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1911</td>\n",
       "      <td>3064</td>\n",
       "      <td>105034.0</td>\n",
       "      <td>3047.0</td>\n",
       "      <td>3918.0</td>\n",
       "      <td>806.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>3578</td>\n",
       "      <td>5689</td>\n",
       "      <td>109697.0</td>\n",
       "      <td>2908.0</td>\n",
       "      <td>2861.0</td>\n",
       "      <td>563.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>6844</td>\n",
       "      <td>10894</td>\n",
       "      <td>131221.0</td>\n",
       "      <td>2802.0</td>\n",
       "      <td>3894.0</td>\n",
       "      <td>865.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>3284</td>\n",
       "      <td>5232</td>\n",
       "      <td>135506.0</td>\n",
       "      <td>2597.0</td>\n",
       "      <td>4486.0</td>\n",
       "      <td>1611.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2744</td>\n",
       "      <td>4370</td>\n",
       "      <td>115048.0</td>\n",
       "      <td>2481.0</td>\n",
       "      <td>3424.0</td>\n",
       "      <td>775.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>8914</td>\n",
       "      <td>14079</td>\n",
       "      <td>93007.0</td>\n",
       "      <td>2189.0</td>\n",
       "      <td>2515.0</td>\n",
       "      <td>479.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>3809</td>\n",
       "      <td>6054</td>\n",
       "      <td>73914.0</td>\n",
       "      <td>2168.0</td>\n",
       "      <td>1592.0</td>\n",
       "      <td>374.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>6532</td>\n",
       "      <td>10392</td>\n",
       "      <td>91341.0</td>\n",
       "      <td>2089.0</td>\n",
       "      <td>2733.0</td>\n",
       "      <td>866.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>3467</td>\n",
       "      <td>5503</td>\n",
       "      <td>68811.0</td>\n",
       "      <td>1944.0</td>\n",
       "      <td>1682.0</td>\n",
       "      <td>328.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>3392</td>\n",
       "      <td>5395</td>\n",
       "      <td>93082.0</td>\n",
       "      <td>1915.0</td>\n",
       "      <td>1719.0</td>\n",
       "      <td>162.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2106</td>\n",
       "      <td>3381</td>\n",
       "      <td>84833.0</td>\n",
       "      <td>1720.0</td>\n",
       "      <td>1627.0</td>\n",
       "      <td>406.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>3985</td>\n",
       "      <td>6344</td>\n",
       "      <td>85369.0</td>\n",
       "      <td>1660.0</td>\n",
       "      <td>3822.0</td>\n",
       "      <td>2208.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2361</td>\n",
       "      <td>3783</td>\n",
       "      <td>62689.0</td>\n",
       "      <td>1553.0</td>\n",
       "      <td>1657.0</td>\n",
       "      <td>375.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>7283</td>\n",
       "      <td>11552</td>\n",
       "      <td>74627.0</td>\n",
       "      <td>1494.0</td>\n",
       "      <td>1654.0</td>\n",
       "      <td>439.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>6619</td>\n",
       "      <td>10533</td>\n",
       "      <td>64242.0</td>\n",
       "      <td>1490.0</td>\n",
       "      <td>1203.0</td>\n",
       "      <td>184.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>3315</td>\n",
       "      <td>5271</td>\n",
       "      <td>64097.0</td>\n",
       "      <td>1484.0</td>\n",
       "      <td>1603.0</td>\n",
       "      <td>339.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>5977</td>\n",
       "      <td>9517</td>\n",
       "      <td>58535.0</td>\n",
       "      <td>1448.0</td>\n",
       "      <td>1397.0</td>\n",
       "      <td>307.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>348</td>\n",
       "      <td>552</td>\n",
       "      <td>60538.0</td>\n",
       "      <td>1392.0</td>\n",
       "      <td>1461.0</td>\n",
       "      <td>488.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>653</td>\n",
       "      <td>1083</td>\n",
       "      <td>66066.0</td>\n",
       "      <td>1385.0</td>\n",
       "      <td>1801.0</td>\n",
       "      <td>530.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>4182</td>\n",
       "      <td>6648</td>\n",
       "      <td>61952.0</td>\n",
       "      <td>1375.0</td>\n",
       "      <td>1390.0</td>\n",
       "      <td>329.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>7471</td>\n",
       "      <td>11824</td>\n",
       "      <td>67306.0</td>\n",
       "      <td>1329.0</td>\n",
       "      <td>1896.0</td>\n",
       "      <td>578.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>5579</td>\n",
       "      <td>8877</td>\n",
       "      <td>63396.0</td>\n",
       "      <td>1247.0</td>\n",
       "      <td>1974.0</td>\n",
       "      <td>1072.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Unnamed: 0  item_category        点击       收藏      加购      支付\n",
       "0         1136           1863  371738.0  10200.0  9309.0  2000.0\n",
       "3         3708           5894  314784.0   7850.0  6615.0   958.0\n",
       "1         8371          13230  342694.0   7226.0  6012.0   841.0\n",
       "2         3148           5027  320870.0   6988.0  5564.0   858.0\n",
       "4         4094           6513  281370.0   6688.0  6651.0  1059.0\n",
       "5         3394           5399  268639.0   6616.0  5430.0  1054.0\n",
       "6         7098          11279  177961.0   4687.0  3686.0   722.0\n",
       "7         1758           2825  155949.0   3360.0  3692.0   625.0\n",
       "13        1911           3064  105034.0   3047.0  3918.0   806.0\n",
       "11        3578           5689  109697.0   2908.0  2861.0   563.0\n",
       "9         6844          10894  131221.0   2802.0  3894.0   865.0\n",
       "8         3284           5232  135506.0   2597.0  4486.0  1611.0\n",
       "10        2744           4370  115048.0   2481.0  3424.0   775.0\n",
       "15        8914          14079   93007.0   2189.0  2515.0   479.0\n",
       "21        3809           6054   73914.0   2168.0  1592.0   374.0\n",
       "16        6532          10392   91341.0   2089.0  2733.0   866.0\n",
       "23        3467           5503   68811.0   1944.0  1682.0   328.0\n",
       "14        3392           5395   93082.0   1915.0  1719.0   162.0\n",
       "18        2106           3381   84833.0   1720.0  1627.0   406.0\n",
       "17        3985           6344   85369.0   1660.0  3822.0  2208.0\n",
       "29        2361           3783   62689.0   1553.0  1657.0   375.0\n",
       "20        7283          11552   74627.0   1494.0  1654.0   439.0\n",
       "26        6619          10533   64242.0   1490.0  1203.0   184.0\n",
       "27        3315           5271   64097.0   1484.0  1603.0   339.0\n",
       "32        5977           9517   58535.0   1448.0  1397.0   307.0\n",
       "31         348            552   60538.0   1392.0  1461.0   488.0\n",
       "25         653           1083   66066.0   1385.0  1801.0   530.0\n",
       "30        4182           6648   61952.0   1375.0  1390.0   329.0\n",
       "24        7471          11824   67306.0   1329.0  1896.0   578.0\n",
       "28        5579           8877   63396.0   1247.0  1974.0  1072.0"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#收藏最多的三十个商品品类\n",
    "data_04 = data_03.copy()\n",
    "data_04.sort_values('收藏',ascending=False,inplace=True) \n",
    "data_04.head(30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>item_category</th>\n",
       "      <th>点击</th>\n",
       "      <th>收藏</th>\n",
       "      <th>加购</th>\n",
       "      <th>支付</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1136</td>\n",
       "      <td>1863</td>\n",
       "      <td>371738.0</td>\n",
       "      <td>10200.0</td>\n",
       "      <td>9309.0</td>\n",
       "      <td>2000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4094</td>\n",
       "      <td>6513</td>\n",
       "      <td>281370.0</td>\n",
       "      <td>6688.0</td>\n",
       "      <td>6651.0</td>\n",
       "      <td>1059.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3708</td>\n",
       "      <td>5894</td>\n",
       "      <td>314784.0</td>\n",
       "      <td>7850.0</td>\n",
       "      <td>6615.0</td>\n",
       "      <td>958.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8371</td>\n",
       "      <td>13230</td>\n",
       "      <td>342694.0</td>\n",
       "      <td>7226.0</td>\n",
       "      <td>6012.0</td>\n",
       "      <td>841.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3148</td>\n",
       "      <td>5027</td>\n",
       "      <td>320870.0</td>\n",
       "      <td>6988.0</td>\n",
       "      <td>5564.0</td>\n",
       "      <td>858.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3394</td>\n",
       "      <td>5399</td>\n",
       "      <td>268639.0</td>\n",
       "      <td>6616.0</td>\n",
       "      <td>5430.0</td>\n",
       "      <td>1054.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>3284</td>\n",
       "      <td>5232</td>\n",
       "      <td>135506.0</td>\n",
       "      <td>2597.0</td>\n",
       "      <td>4486.0</td>\n",
       "      <td>1611.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1911</td>\n",
       "      <td>3064</td>\n",
       "      <td>105034.0</td>\n",
       "      <td>3047.0</td>\n",
       "      <td>3918.0</td>\n",
       "      <td>806.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>6844</td>\n",
       "      <td>10894</td>\n",
       "      <td>131221.0</td>\n",
       "      <td>2802.0</td>\n",
       "      <td>3894.0</td>\n",
       "      <td>865.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>3985</td>\n",
       "      <td>6344</td>\n",
       "      <td>85369.0</td>\n",
       "      <td>1660.0</td>\n",
       "      <td>3822.0</td>\n",
       "      <td>2208.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1758</td>\n",
       "      <td>2825</td>\n",
       "      <td>155949.0</td>\n",
       "      <td>3360.0</td>\n",
       "      <td>3692.0</td>\n",
       "      <td>625.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7098</td>\n",
       "      <td>11279</td>\n",
       "      <td>177961.0</td>\n",
       "      <td>4687.0</td>\n",
       "      <td>3686.0</td>\n",
       "      <td>722.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2744</td>\n",
       "      <td>4370</td>\n",
       "      <td>115048.0</td>\n",
       "      <td>2481.0</td>\n",
       "      <td>3424.0</td>\n",
       "      <td>775.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>5976</td>\n",
       "      <td>9516</td>\n",
       "      <td>81285.0</td>\n",
       "      <td>1230.0</td>\n",
       "      <td>3340.0</td>\n",
       "      <td>828.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>3578</td>\n",
       "      <td>5689</td>\n",
       "      <td>109697.0</td>\n",
       "      <td>2908.0</td>\n",
       "      <td>2861.0</td>\n",
       "      <td>563.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>4996</td>\n",
       "      <td>7957</td>\n",
       "      <td>42555.0</td>\n",
       "      <td>883.0</td>\n",
       "      <td>2745.0</td>\n",
       "      <td>997.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>6532</td>\n",
       "      <td>10392</td>\n",
       "      <td>91341.0</td>\n",
       "      <td>2089.0</td>\n",
       "      <td>2733.0</td>\n",
       "      <td>866.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>8914</td>\n",
       "      <td>14079</td>\n",
       "      <td>93007.0</td>\n",
       "      <td>2189.0</td>\n",
       "      <td>2515.0</td>\n",
       "      <td>479.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>4394</td>\n",
       "      <td>6977</td>\n",
       "      <td>22806.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>1324.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>5579</td>\n",
       "      <td>8877</td>\n",
       "      <td>63396.0</td>\n",
       "      <td>1247.0</td>\n",
       "      <td>1974.0</td>\n",
       "      <td>1072.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>7471</td>\n",
       "      <td>11824</td>\n",
       "      <td>67306.0</td>\n",
       "      <td>1329.0</td>\n",
       "      <td>1896.0</td>\n",
       "      <td>578.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>653</td>\n",
       "      <td>1083</td>\n",
       "      <td>66066.0</td>\n",
       "      <td>1385.0</td>\n",
       "      <td>1801.0</td>\n",
       "      <td>530.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>3392</td>\n",
       "      <td>5395</td>\n",
       "      <td>93082.0</td>\n",
       "      <td>1915.0</td>\n",
       "      <td>1719.0</td>\n",
       "      <td>162.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2164</td>\n",
       "      <td>3472</td>\n",
       "      <td>51456.0</td>\n",
       "      <td>823.0</td>\n",
       "      <td>1707.0</td>\n",
       "      <td>1038.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>1124</td>\n",
       "      <td>1838</td>\n",
       "      <td>52076.0</td>\n",
       "      <td>850.0</td>\n",
       "      <td>1687.0</td>\n",
       "      <td>919.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>3467</td>\n",
       "      <td>5503</td>\n",
       "      <td>68811.0</td>\n",
       "      <td>1944.0</td>\n",
       "      <td>1682.0</td>\n",
       "      <td>328.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2361</td>\n",
       "      <td>3783</td>\n",
       "      <td>62689.0</td>\n",
       "      <td>1553.0</td>\n",
       "      <td>1657.0</td>\n",
       "      <td>375.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>7283</td>\n",
       "      <td>11552</td>\n",
       "      <td>74627.0</td>\n",
       "      <td>1494.0</td>\n",
       "      <td>1654.0</td>\n",
       "      <td>439.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2253</td>\n",
       "      <td>3628</td>\n",
       "      <td>70260.0</td>\n",
       "      <td>1221.0</td>\n",
       "      <td>1641.0</td>\n",
       "      <td>583.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2106</td>\n",
       "      <td>3381</td>\n",
       "      <td>84833.0</td>\n",
       "      <td>1720.0</td>\n",
       "      <td>1627.0</td>\n",
       "      <td>406.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Unnamed: 0  item_category        点击       收藏      加购      支付\n",
       "0         1136           1863  371738.0  10200.0  9309.0  2000.0\n",
       "4         4094           6513  281370.0   6688.0  6651.0  1059.0\n",
       "3         3708           5894  314784.0   7850.0  6615.0   958.0\n",
       "1         8371          13230  342694.0   7226.0  6012.0   841.0\n",
       "2         3148           5027  320870.0   6988.0  5564.0   858.0\n",
       "5         3394           5399  268639.0   6616.0  5430.0  1054.0\n",
       "8         3284           5232  135506.0   2597.0  4486.0  1611.0\n",
       "13        1911           3064  105034.0   3047.0  3918.0   806.0\n",
       "9         6844          10894  131221.0   2802.0  3894.0   865.0\n",
       "17        3985           6344   85369.0   1660.0  3822.0  2208.0\n",
       "7         1758           2825  155949.0   3360.0  3692.0   625.0\n",
       "6         7098          11279  177961.0   4687.0  3686.0   722.0\n",
       "10        2744           4370  115048.0   2481.0  3424.0   775.0\n",
       "19        5976           9516   81285.0   1230.0  3340.0   828.0\n",
       "11        3578           5689  109697.0   2908.0  2861.0   563.0\n",
       "43        4996           7957   42555.0    883.0  2745.0   997.0\n",
       "16        6532          10392   91341.0   2089.0  2733.0   866.0\n",
       "15        8914          14079   93007.0   2189.0  2515.0   479.0\n",
       "87        4394           6977   22806.0    273.0  2007.0  1324.0\n",
       "28        5579           8877   63396.0   1247.0  1974.0  1072.0\n",
       "24        7471          11824   67306.0   1329.0  1896.0   578.0\n",
       "25         653           1083   66066.0   1385.0  1801.0   530.0\n",
       "14        3392           5395   93082.0   1915.0  1719.0   162.0\n",
       "35        2164           3472   51456.0    823.0  1707.0  1038.0\n",
       "34        1124           1838   52076.0    850.0  1687.0   919.0\n",
       "23        3467           5503   68811.0   1944.0  1682.0   328.0\n",
       "29        2361           3783   62689.0   1553.0  1657.0   375.0\n",
       "20        7283          11552   74627.0   1494.0  1654.0   439.0\n",
       "22        2253           3628   70260.0   1221.0  1641.0   583.0\n",
       "18        2106           3381   84833.0   1720.0  1627.0   406.0"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#加购最多的三十个商品品类\n",
    "data_05 = data_03.copy()\n",
    "data_05.sort_values('加购',ascending=False,inplace=True)  \n",
    "data_05.head(30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "      <th>e</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>803231</td>\n",
       "      <td>112921337</td>\n",
       "      <td>1431.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>694445</td>\n",
       "      <td>97655171</td>\n",
       "      <td>1249.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2758493</td>\n",
       "      <td>387911330</td>\n",
       "      <td>1053.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>960291</td>\n",
       "      <td>135104537</td>\n",
       "      <td>916.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>15965</td>\n",
       "      <td>2217535</td>\n",
       "      <td>792.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>40785</td>\n",
       "      <td>5685392</td>\n",
       "      <td>767.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>911711</td>\n",
       "      <td>128186279</td>\n",
       "      <td>765.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1976225</td>\n",
       "      <td>277922302</td>\n",
       "      <td>763.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>100264</td>\n",
       "      <td>14087919</td>\n",
       "      <td>740.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>35.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1488679</td>\n",
       "      <td>209323160</td>\n",
       "      <td>716.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1958544</td>\n",
       "      <td>275450912</td>\n",
       "      <td>665.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2661450</td>\n",
       "      <td>374235261</td>\n",
       "      <td>634.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2512342</td>\n",
       "      <td>353381230</td>\n",
       "      <td>606.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1506245</td>\n",
       "      <td>211781109</td>\n",
       "      <td>603.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2293838</td>\n",
       "      <td>322554659</td>\n",
       "      <td>593.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>47968</td>\n",
       "      <td>6703599</td>\n",
       "      <td>589.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1544736</td>\n",
       "      <td>217213194</td>\n",
       "      <td>567.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>150036</td>\n",
       "      <td>21087251</td>\n",
       "      <td>544.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2525865</td>\n",
       "      <td>355292943</td>\n",
       "      <td>538.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2156381</td>\n",
       "      <td>303205878</td>\n",
       "      <td>534.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2489530</td>\n",
       "      <td>350186246</td>\n",
       "      <td>527.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>472078</td>\n",
       "      <td>66399540</td>\n",
       "      <td>525.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2239215</td>\n",
       "      <td>314903844</td>\n",
       "      <td>520.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>893767</td>\n",
       "      <td>125666923</td>\n",
       "      <td>516.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1966940</td>\n",
       "      <td>276636269</td>\n",
       "      <td>509.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2571536</td>\n",
       "      <td>361681874</td>\n",
       "      <td>508.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1762675</td>\n",
       "      <td>247894113</td>\n",
       "      <td>500.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>194830</td>\n",
       "      <td>27364659</td>\n",
       "      <td>491.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>771063</td>\n",
       "      <td>108385699</td>\n",
       "      <td>487.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1310204</td>\n",
       "      <td>184181655</td>\n",
       "      <td>483.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Unnamed: 0          a       b     c     d     e\n",
       "0       803231  112921337  1431.0   5.0   8.0   1.0\n",
       "1       694445   97655171  1249.0   7.0  20.0  13.0\n",
       "2      2758493  387911330  1053.0  10.0  20.0  19.0\n",
       "3       960291  135104537   916.0   7.0   8.0   0.0\n",
       "4        15965    2217535   792.0   1.0  11.0   1.0\n",
       "5        40785    5685392   767.0  12.0  12.0   2.0\n",
       "6       911711  128186279   765.0  13.0  16.0   1.0\n",
       "7      1976225  277922302   763.0  24.0  20.0   1.0\n",
       "8       100264   14087919   740.0  15.0  33.0  35.0\n",
       "9      1488679  209323160   716.0   2.0  26.0   0.0\n",
       "10     1958544  275450912   665.0   5.0   2.0   0.0\n",
       "11     2661450  374235261   634.0   5.0   6.0   1.0\n",
       "12     2512342  353381230   606.0   9.0  31.0   5.0\n",
       "13     1506245  211781109   603.0  14.0  20.0   1.0\n",
       "14     2293838  322554659   593.0   6.0   8.0   1.0\n",
       "15       47968    6703599   589.0  17.0  15.0   2.0\n",
       "16     1544736  217213194   567.0   4.0   7.0   0.0\n",
       "17      150036   21087251   544.0  13.0  11.0   2.0\n",
       "18     2525865  355292943   538.0  12.0  12.0   5.0\n",
       "19     2156381  303205878   534.0  11.0  46.0  50.0\n",
       "20     2489530  350186246   527.0   5.0   7.0   0.0\n",
       "21      472078   66399540   525.0   4.0  23.0   6.0\n",
       "22     2239215  314903844   520.0   5.0  12.0  13.0\n",
       "23      893767  125666923   516.0  10.0  23.0   5.0\n",
       "24     1966940  276636269   509.0  15.0  15.0  16.0\n",
       "25     2571536  361681874   508.0   5.0  16.0  10.0\n",
       "26     1762675  247894113   500.0   8.0  11.0   0.0\n",
       "27      194830   27364659   491.0   5.0   5.0   0.0\n",
       "28      771063  108385699   487.0  15.0   5.0   2.0\n",
       "29     1310204  184181655   483.0  12.0   8.0   0.0"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#点击最高的三十个商品\n",
    "data_06 = pd.read_csv('./每种商品的点击量、收藏量、加购量、购买量.csv')\n",
    "data_06.sort_values('b',ascending=False,inplace = True)\n",
    "data_06.head(30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "      <th>e</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2156381</td>\n",
       "      <td>303205878</td>\n",
       "      <td>534.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>100264</td>\n",
       "      <td>14087919</td>\n",
       "      <td>740.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>35.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67276</th>\n",
       "      <td>818835</td>\n",
       "      <td>115124482</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11454</th>\n",
       "      <td>1728268</td>\n",
       "      <td>243091690</td>\n",
       "      <td>54.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>29.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>1188146</td>\n",
       "      <td>167074648</td>\n",
       "      <td>429.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2108</th>\n",
       "      <td>777261</td>\n",
       "      <td>109259240</td>\n",
       "      <td>119.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35696</th>\n",
       "      <td>909780</td>\n",
       "      <td>127914633</td>\n",
       "      <td>29.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13772</th>\n",
       "      <td>724135</td>\n",
       "      <td>101795752</td>\n",
       "      <td>49.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>2661308</td>\n",
       "      <td>374214353</td>\n",
       "      <td>320.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22590</th>\n",
       "      <td>2349887</td>\n",
       "      <td>330469986</td>\n",
       "      <td>38.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>582</th>\n",
       "      <td>1255692</td>\n",
       "      <td>176556528</td>\n",
       "      <td>196.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61218</th>\n",
       "      <td>121351</td>\n",
       "      <td>17065447</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114920</th>\n",
       "      <td>2846568</td>\n",
       "      <td>400291504</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15579</th>\n",
       "      <td>2728907</td>\n",
       "      <td>383779671</td>\n",
       "      <td>46.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1085</th>\n",
       "      <td>2358711</td>\n",
       "      <td>331710542</td>\n",
       "      <td>155.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56591</th>\n",
       "      <td>1339037</td>\n",
       "      <td>188241513</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1119</th>\n",
       "      <td>2774562</td>\n",
       "      <td>390181058</td>\n",
       "      <td>153.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215</th>\n",
       "      <td>513247</td>\n",
       "      <td>72183675</td>\n",
       "      <td>280.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>590721</td>\n",
       "      <td>83098075</td>\n",
       "      <td>470.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>374518</th>\n",
       "      <td>2538470</td>\n",
       "      <td>357062464</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112580</th>\n",
       "      <td>2170715</td>\n",
       "      <td>305229489</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2758493</td>\n",
       "      <td>387911330</td>\n",
       "      <td>1053.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10812</th>\n",
       "      <td>1427349</td>\n",
       "      <td>200630531</td>\n",
       "      <td>56.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>966</th>\n",
       "      <td>2264960</td>\n",
       "      <td>318515601</td>\n",
       "      <td>161.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>309</th>\n",
       "      <td>1138658</td>\n",
       "      <td>160115566</td>\n",
       "      <td>245.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>622494</td>\n",
       "      <td>87546522</td>\n",
       "      <td>314.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33169</th>\n",
       "      <td>188683</td>\n",
       "      <td>26492860</td>\n",
       "      <td>31.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>226933</th>\n",
       "      <td>1825696</td>\n",
       "      <td>256794605</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193283</th>\n",
       "      <td>2173547</td>\n",
       "      <td>305623947</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5535</th>\n",
       "      <td>1577587</td>\n",
       "      <td>221830759</td>\n",
       "      <td>77.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Unnamed: 0          a       b     c     d     e\n",
       "19         2156381  303205878   534.0  11.0  46.0  50.0\n",
       "8           100264   14087919   740.0  15.0  33.0  35.0\n",
       "67276       818835  115124482    20.0   0.0   0.0  31.0\n",
       "11454      1728268  243091690    54.0   2.0   3.0  29.0\n",
       "45         1188146  167074648   429.0   4.0  19.0  28.0\n",
       "2108        777261  109259240   119.0   0.0  14.0  24.0\n",
       "35696       909780  127914633    29.0   0.0   4.0  24.0\n",
       "13772       724135  101795752    49.0   0.0   4.0  23.0\n",
       "139        2661308  374214353   320.0   2.0  32.0  23.0\n",
       "22590      2349887  330469986    38.0   2.0   1.0  22.0\n",
       "582        1255692  176556528   196.0   3.0  11.0  22.0\n",
       "61218       121351   17065447    21.0   0.0   3.0  22.0\n",
       "114920     2846568  400291504    14.0   0.0   3.0  22.0\n",
       "15579      2728907  383779671    46.0   1.0   0.0  22.0\n",
       "1085       2358711  331710542   155.0   0.0   0.0  21.0\n",
       "56591      1339037  188241513    22.0   0.0   2.0  21.0\n",
       "1119       2774562  390181058   153.0   2.0  16.0  21.0\n",
       "215         513247   72183675   280.0   3.0  31.0  20.0\n",
       "32          590721   83098075   470.0   3.0  56.0  20.0\n",
       "374518     2538470  357062464     6.0   0.0   1.0  19.0\n",
       "112580     2170715  305229489    14.0   0.0   3.0  19.0\n",
       "2          2758493  387911330  1053.0  10.0  20.0  19.0\n",
       "10812      1427349  200630531    56.0   0.0   4.0  18.0\n",
       "966        2264960  318515601   161.0   1.0   9.0  18.0\n",
       "309        1138658  160115566   245.0   4.0  16.0  18.0\n",
       "149         622494   87546522   314.0   6.0  19.0  18.0\n",
       "33169       188683   26492860    31.0   0.0   6.0  18.0\n",
       "226933     1825696  256794605     9.0   0.0   6.0  18.0\n",
       "193283     2173547  305623947    10.0   0.0   3.0  17.0\n",
       "5535       1577587  221830759    77.0   1.0   4.0  17.0"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#购买最多的三十个商品\n",
    "data_07 = data_06.copy()\n",
    "data_07.sort_values('e',ascending=False,inplace=True)  \n",
    "data_07.head(30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_07.rename(columns={'a':'商品编号','b':'点击','c':'收藏','d':'加购','e':'购买'},inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>商品编号</th>\n",
       "      <th>点击</th>\n",
       "      <th>收藏</th>\n",
       "      <th>加购</th>\n",
       "      <th>购买</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2156381</td>\n",
       "      <td>303205878</td>\n",
       "      <td>534.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>100264</td>\n",
       "      <td>14087919</td>\n",
       "      <td>740.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>35.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67276</th>\n",
       "      <td>818835</td>\n",
       "      <td>115124482</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11454</th>\n",
       "      <td>1728268</td>\n",
       "      <td>243091690</td>\n",
       "      <td>54.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>29.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>1188146</td>\n",
       "      <td>167074648</td>\n",
       "      <td>429.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2108</th>\n",
       "      <td>777261</td>\n",
       "      <td>109259240</td>\n",
       "      <td>119.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35696</th>\n",
       "      <td>909780</td>\n",
       "      <td>127914633</td>\n",
       "      <td>29.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13772</th>\n",
       "      <td>724135</td>\n",
       "      <td>101795752</td>\n",
       "      <td>49.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>2661308</td>\n",
       "      <td>374214353</td>\n",
       "      <td>320.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22590</th>\n",
       "      <td>2349887</td>\n",
       "      <td>330469986</td>\n",
       "      <td>38.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>582</th>\n",
       "      <td>1255692</td>\n",
       "      <td>176556528</td>\n",
       "      <td>196.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61218</th>\n",
       "      <td>121351</td>\n",
       "      <td>17065447</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114920</th>\n",
       "      <td>2846568</td>\n",
       "      <td>400291504</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15579</th>\n",
       "      <td>2728907</td>\n",
       "      <td>383779671</td>\n",
       "      <td>46.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1085</th>\n",
       "      <td>2358711</td>\n",
       "      <td>331710542</td>\n",
       "      <td>155.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56591</th>\n",
       "      <td>1339037</td>\n",
       "      <td>188241513</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1119</th>\n",
       "      <td>2774562</td>\n",
       "      <td>390181058</td>\n",
       "      <td>153.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215</th>\n",
       "      <td>513247</td>\n",
       "      <td>72183675</td>\n",
       "      <td>280.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>590721</td>\n",
       "      <td>83098075</td>\n",
       "      <td>470.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>374518</th>\n",
       "      <td>2538470</td>\n",
       "      <td>357062464</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Unnamed: 0       商品编号     点击    收藏    加购    购买\n",
       "19         2156381  303205878  534.0  11.0  46.0  50.0\n",
       "8           100264   14087919  740.0  15.0  33.0  35.0\n",
       "67276       818835  115124482   20.0   0.0   0.0  31.0\n",
       "11454      1728268  243091690   54.0   2.0   3.0  29.0\n",
       "45         1188146  167074648  429.0   4.0  19.0  28.0\n",
       "2108        777261  109259240  119.0   0.0  14.0  24.0\n",
       "35696       909780  127914633   29.0   0.0   4.0  24.0\n",
       "13772       724135  101795752   49.0   0.0   4.0  23.0\n",
       "139        2661308  374214353  320.0   2.0  32.0  23.0\n",
       "22590      2349887  330469986   38.0   2.0   1.0  22.0\n",
       "582        1255692  176556528  196.0   3.0  11.0  22.0\n",
       "61218       121351   17065447   21.0   0.0   3.0  22.0\n",
       "114920     2846568  400291504   14.0   0.0   3.0  22.0\n",
       "15579      2728907  383779671   46.0   1.0   0.0  22.0\n",
       "1085       2358711  331710542  155.0   0.0   0.0  21.0\n",
       "56591      1339037  188241513   22.0   0.0   2.0  21.0\n",
       "1119       2774562  390181058  153.0   2.0  16.0  21.0\n",
       "215         513247   72183675  280.0   3.0  31.0  20.0\n",
       "32          590721   83098075  470.0   3.0  56.0  20.0\n",
       "374518     2538470  357062464    6.0   0.0   1.0  19.0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_07.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
